Unless otherwise indicated herein, the materials described in this section are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section.
Trends toward unification of cloud based services include coding and standards frameworks that allow customers to move from one datacenter provider to another. Datacenter brokers are increasingly common entities who work to capture better deals for clients and thus are making the tasks more mobile. At the same time, a cloud vendor may wish to sell the highest Quality of Service (QoS) it can perform in order to raise pricing, but when new work arrives with a higher requested QoS, the new work may mean rejecting ongoing lower QoS work to clear resources and thus being left with empty processors once the high QoS work is completed.
Cloud computing resources are provided in imprecise unit measures. Examples include memory, bit width, and rough I/O performance, but do not usually specify processor types, for example. “Equivalent processing power” and I/O performance are measured in granularity as rough as Low/Medium/High, which means that complex distributed applications may perform differently on different clouds, even on identically specified and priced computing units. One service provider's equivalent instances may be faster at CPU than another provider's, but slower in storage 110. The relative performance difference between identically specified clouds may change over time due to internal network congestion, equipment replacement, and even usage level.
There presently are shortcomings in conventional datacenter management methods. For example, the difference in performance raises the possibility of arbitrage—taking advantage of a value difference between markets using better information. If a user has a true measure of how much work their application can perform for a given price on different clouds, they may choose the cheapest and thereby save money purely by informational advantage.